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Clustering of exchange rates and their dynamics under different dependence measures
Renedo, Martí; Arratia Quesada, Argimiro Alejandro
Universitat Politècnica de Catalunya. Departament de Ciències de la Computació; Universitat Politècnica de Catalunya. LARCA - Laboratori d'Algorísmia Relacional, Complexitat i Aprenentatge
This paper proposes an improvement to the method for clustering exchange rates given by D. J. Fenn et al, in Quantitative Finance, 12 (10) 2012, pp.1493-1520. To deal with the potentially non linear nature of currency time series dependence, we propose two alternative similarity metrics to use instead of the one used in the aforementioned paper based on Pearson correlation. Our proposed similarity metrics are based upon Kendall and distance correlations. We observe how each of the newly adapted clustering methods respond over several years of currency exchange data and find significant differences in the resulting clusters.
Peer Reviewed
Àrees temàtiques de la UPC::Matemàtiques i estadística
Àrees temàtiques de la UPC::Economia i organització d'empreses::Macroeconomia::Finances
Foreign exchange market
Data mining
Community detection
Distance correlation
Kendall correlation
FX market
Mercats financers
Mineria de dades

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